iCarMa

Abstract

Ubiquity of smartphones with array of inbuilt sensors, pave ways to inexpensive mobile-health systems, particularly for cardio-vascular health monitoring. Smartphones, wearable sensors, and body area sensors play an important role as a part of Internet of Things (IoT) m-health ecosystem. In this paper, we present iCarMa to enable an inexpensive auto-triggered arrhythmia cardiac management solution catering the need of in-house, round-the-clock cardiac health monitoring. It facilitates early detection of fatal cardiac conditions like asystole, extreme bradycardia, extreme tachycardia, ventricular flutter and ventricular tachycardia, which often compel an individual to get admitted in Intensive Care Unit (ICU). Smartphone or wearable sensor extracted photoplethysmogram (PPG) is the sole physiological signal that is considered to characterize the cardiac anomalous events. Our main novelty is to precisely detect and remove the motion artifacts in PPG signals and to ensure accuracy in arrhythmia condition detection, specifically to reduce the false negative alarms. We establish the efficacy of proposed solution, iCarMa by large set of experiments with field-collected and MIT-Physionet PPG signals.